{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2ce61bb5-1d5b-43b8-b5bb-6aeae91c7574",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "from IPython.display import Markdown, display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3399686d-5f14-4fb2-8939-fd2401be3007",
   "metadata": {},
   "outputs": [],
   "source": [
    "MODEL = \"gpt-4o-mini\"\n",
    "SYSTEM_PROMPT_PATH = \"Chat_Summary_Data/System_Prompt.txt\"\n",
    "CHATS_PATH = \"Chat_Summary_Data/Chat_Examples/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d97b8374-a161-435c-8317-1d0ecaaa9b71",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "API key found and looks good so far!\n"
     ]
    }
   ],
   "source": [
    "# Load environment variables in a file called .env\n",
    "\n",
    "load_dotenv(override=True)\n",
    "api_key = os.getenv('OPENAI_API_KEY')\n",
    "\n",
    "# Check the key\n",
    "\n",
    "if not api_key:\n",
    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
    "elif not api_key.startswith(\"sk-proj-\"):\n",
    "    print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
    "elif api_key.strip() != api_key:\n",
    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
    "else:\n",
    "    print(\"API key found and looks good so far!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b3f4afb4-2e4a-4971-915e-a8634a17eda8",
   "metadata": {},
   "outputs": [],
   "source": [
    "class ChatAI:\n",
    "    def __init__(self, system_prompt_path=SYSTEM_PROMPT_PATH, model=MODEL):\n",
    "        with open(system_prompt_path, \"r\") as file:\n",
    "            self.system_prompt = file.read()\n",
    "\n",
    "        self.openai = OpenAI()\n",
    "        self.model = model\n",
    "        \n",
    "    @staticmethod\n",
    "    def _get_user_prompt(chat_txt):\n",
    "        with open(chat_txt, \"r\") as file:\n",
    "            user_prompt_str = file.read()\n",
    "        return user_prompt_str\n",
    "    \n",
    "    def generate(self, chat_txt):\n",
    "        messages = [\n",
    "            {\"role\": \"system\", \"content\": self.system_prompt},\n",
    "            {\"role\": \"user\", \"content\": self._get_user_prompt(chat_txt)}\n",
    "        ]\n",
    "\n",
    "        response = self.openai.chat.completions.create(model=self.model, messages=messages)\n",
    "        return response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d243b582-66af-49f9-bcd1-e05a63e61c34",
   "metadata": {},
   "outputs": [],
   "source": [
    "chat_ai = ChatAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c764ace6-5a0f-4dd0-9454-0b8a093b97fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "# Chat1"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "- **Order:** 2 Medium Chicken BBQ Pizzas\n",
       "- **Cost:** 342 LE\n",
       "- **Experience:** Negative\n",
       "  - **Summary:** The client expressed dissatisfaction with the pizza taste."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "# Chat2"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "- The client ordered: Nothing \n",
       "- Summary: The client did not place an order because the chicken ranch pizza was unavailable."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "# Chat3"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "- **Order**: Large pepperoni pizza and onion rings  \n",
       "- **Total Cost**: 250 LE  \n",
       "- **Experience**: Positive  \n",
       "  - The client enjoyed the pizza despite the delay in delivery."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "chats_txt = os.listdir(CHATS_PATH)\n",
    "for chat_file in chats_txt:\n",
    "    markdown_heading = f\"# {chat_file[:-4]}\"\n",
    "    display(Markdown(markdown_heading))\n",
    "    display(Markdown(chat_ai.generate(CHATS_PATH+chat_file)))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
